The Learning With Error problem (LWE) is becoming more and more used in cryptography, for instance, in the design of some fully homomorphic encryption schemes. It is thus of primordial importance to find the best algorithms that might solve this problem so that concrete parameters can be proposed. The BKW algorithm was proposed by Blum et al. as an algorithm to solve the Learning Parity with Noise problem (LPN), a subproblem of LWE. This algorithm was then adapted to LWE by Albrecht et al.

In this paper, we improve the algorithm proposed by Albrecht et al. by using multidimensional Fourier transforms. Our algorithm is, to the best of our knowledge, the fastest LWE solving algorithm. Compared to the work of Albrecht et al. we greatly simplify the analysis, getting rid of integrals which were hard to evaluate in the final complexity. We also remove some heuristics on rounded Gaussians. Some of our results on rounded Gaussians might be of independent interest. Moreover, we also analyze algorithms solving LWE with discrete Gaussian noise.

Finally, we apply the same algorithm to the Learning With Rounding problem (LWR) for prime q, a deterministic counterpart to LWE. This problem is getting more and more attention and is used, for instance, to design pseudorandom functions. To the best of our knowledge, our algorithm is the first algorithm applied directly to LWR. Furthermore, the analysis of LWR contains some technical results of independent interest.

We design a linearly homomorphic encryption scheme whose security relies on the hardness of the decisional Diffie-Hellman problem. Our approach requires some special features of the underlying group. In particular, its order is unknown and it contains a subgroup in which the discrete logarithm problem is tractable. Therefore, our instantiation holds in the class group of a non maximal order of an imaginary quadratic field. Its algebraic structure makes it possible to obtain such a linearly homomorphic scheme whose message space is the whole set of integers modulo a prime p and which supports an unbounded number of additions modulo p from the ciphertexts. A notable difference with previous works is that, for the first time, the security does not depend on the hardness of the factorization of integers. As a consequence, under some conditions, the prime p can be scaled to fit the application needs.

Assuming trapdoor permutations, we show that there exist function families that cannot be VBB-obfuscated even if both the obfuscator and the obfuscated program have access to a random oracle. Specifically, these families are the robust unobfuscatable families of [Bitansky-Paneth, STOC 13].

The Learning Parity with Noise problem (LPN) is appealing in cryptography as it is considered to remain hard in the post-quantum world. It is also a good candidate for lightweight devices due to its simplicity. In this paper we provide a comprehensive analysis of the existing LPN solving algorithms, both for the general case and for the sparse secret scenario. In practice, the LPN-based cryptographic constructions use as a reference the security parameters proposed by Levieil and Fouque. But, for these parameters, there remains a gap between the theoretical analysis and the practical complexities of the algorithms we consider. The new theoretical analysis in this paper provides tighter bounds on the complexity of LPN solving algorithms and narrows this gap between theory and practice. We show that for a sparse secret there is another algorithm that outperforms BKW and its variants. Following from our results, we further propose practical parameters for different security levels.

Groth, Ostrovsky and Sahai constructed a non-interactive Zap for NP-languages by observing that

the common reference string of their proof system for circuit satisfiability admits what they call correlated key generation.

The latter means that it is possible to create from scratch two common reference strings in such a way that it can be publicly verified that at least one of them guarantees perfect soundness while

it is computationally infeasible to tell which one. Their technique also implies that it is possible to have NIWI Groth-Sahai proofs for certain types of equations over bilinear groups in the plain model. We extend the result of Groth, Ostrovsky and Sahai in several directions. Given as input some predicate $P$ computable by some monotone span program over a finite field, we show how to generate a set of common reference strings in such a way that it can be publicly verified that the subset of them which guarantees perfect soundness is accepted by the span program. We give several different flavors of the technique suitable for different applications scenarios and different equation types. We use this to stretch the expressivity of Groth-Sahai proofs and construct NIZK proofs of partial satisfiability of sets of equations in a bilinear group and more efficient Groth-Sahai NIWI proofs without common reference string for a larger class of equation types. Finally, we apply our results to significantly reduce the size of the signatures of the ring signature scheme of Chandran, Groth and Sahai or to have a more efficient proof in the standard model that a commitment opens to an element of a public list.

Improved meet-in-the-middle cryptanalysis with efficient tabulation technique has been shown to be a very powerful form of cryptanalysis against SPN block ciphers. However, few literatures show the effectiveness of this cryptanalysis against Balanced-Feistel-Networks (BFN) and Generalized-Feistel-Networks (GFN) ciphers due to the stagger of affected trail and special truncated differential trail. In this paper, we describe a versatile and powerful algorithm for searching the best improved meet-in-the-middle distinguisher with efficient tabulation technique on word-oriented BFN and GFN block ciphers, which is based on recursion and greedy algorithm. To demonstrate the usefulness of our approach, we show key recovery attacks on 14/16-round CLEFIA-192/256 which are the best attacks. We also propose key recovery attacks on 13/15-round Camellia-192/256 (without $FL/FL^{-1}$).

This paper considers the problem of secure storage of outsourced data in a way that permits deduplication. We are for the first time able to provide privacy for messages that are both correlated and dependent on the public system parameters. The new ingredient that makes this possible is interaction. We extend the message-locked encryption (MLE) primitive of prior work to interactive message-locked encryption (iMLE) where upload and download are protocols. Our scheme, providing security for messages that are not only correlated but allowed to depend on the public system parameters, is in the standard model. We explain that interaction is not an extra assumption in practice because full, existing deduplication systems are already interactive.

Group signature is a class of digital signatures with enhanced privacy. By using this type of signature, a user can prove membership of a specific group without revealing his identity, but in the case of a dispute, for a given signature, an authority can expose the identity of its signer. However, in some situations wherein it is necessary to only know whether a specified user is the signer of the given signature, the naive use of a group signature may be problematic since if the specified user is NOT the actual signer, then the identity of the actual signer will be exposed.

In this paper, inspired by this problem, we propose the notion of a deniable group signature, where with respect to a signature and a user, the opener can issue a proof that the opening result of the signature is NOT the specified user without revealing the actual signer. We also describe a fairly practical construction by extending the Groth group signature scheme (ASIACRYPT 2007). In particular, a denial proof in our scheme consists of 96 group elements, which is about twice the size of a signature in the Groth scheme. The proposed scheme is provably secure under the same assumptions as those of the Groth scheme.

Many cryptographic protocols derive their security from the apparent computational intractability of the integer factorization problem. Currently, the best known integer-factoring algorithms run in subexponential time. Efficient parallel implementations of these algorithms constitute an important area of practical research. Most reported implementations use multi-core and/or distributed parallelization. In this paper, we use SIMD-based parallelization to speed up the sieving stage of integer-factoring algorithms. We experiment on the two fastest variants of factoring algorithms: the number-field sieve method and the multiple-polynomial quadratic sieve method. Using Intel\'s SSE2 and AVX intrinsics, we have been able to speed up index calculations in each core during sieving. This performance enhancement is attributed to a reduction in the packing and unpacking overheads associated with SIMD registers. We handle both line sieving and lattice sieving. We also propose improvements to make our implementations cache-friendly. We obtain speedup figures in the range 5--40%. To the best of our knowledge, no public discussions on SIMD parallelization in the context of integer-factoring algorithms are available in the literature.